Microplastics can have several negative consequences on a variety of organisms, and their prevalence in marine ecosystems has become a major concern. Researchers have recently focused their attention on the world's largest gulf, the Gulf of Mexico (GoM), to determine and assess the impact of microplastic pollution on various environmental compartments (i.e., water, sediment, and biota). This paper critically reviews the analytical methodologies as well as summarizes the distribution, accumulation, sources, and composition of microplastics in a handful of studies (n = 14) conducted in the Gulf of Mexico (GoM) covering countries like the USA (n = 10) and Mexico (n = 4). Current quality control measures with respect to sampling and microplastic extraction are summarized. Of 14 studies reviewed, 47% primarily focused on examining sediments for microplastics, with biota and water comprising 35% and 18%, respectively. The abundance ranged from 31.7 to 1392 items m⁻² and 60–1940 items kg⁻¹ in sediment, 12–381 particles L⁻¹ in water, and 1.31–4.7 particles per fish in biota. Irregular shaped fragments were the most abundant, followed by fiber, film, foam, hard, and beads etc. Different polymer types of microplastics have been found, including polyethylene, polypropylene, polystyrene, polyamide, nylon, and rayon etc. According to published research, 46 out of 100 fish thriving in this region are susceptible to microplastic ingestion. Although microplastic concentration in the GoM is among the highest found worldwide, the determination of microplastic contamination is still a growing field of research and methodological discrepancies largely limit the realization of establishing a baseline information on the microplastic abundance of the GoM. In this respect, considerable efforts must be dedicated towards evaluating their distribution and exposure levels; thereby, major challenges and future research directions are briefly discussed.

This research apportioned size-resolved particulate matter (PM) contributions in a megacity in northern China based on a full year of measurements of both inorganic and organic markers. Ions, elements, carbon fractions, n-alkanes, polycyclic aromatic hydrocarbons (PAHs), hopanes and steranes in 9 p.m. size fractions were analyzed. High molecular weight PAHs concentrated in fine PM, while most other organic compounds showed two peaks. Both two-way and three-way receptor models were used for source apportionment of PM in different size ranges. The three-way receptor model gave a clearer separation of factors than the two-way model, because it uses a combination of chemical composition and size distributions, so that factors with similar composition but distinct size distributions (like more mature and less mature coal combustion) can be resolved. The three-way model resolved six primary and three secondary factors. Gasoline vehicles and coal and biomass combustion, nitrate and high relative humidity related secondary aerosol, and resuspended dust and diesel vehicles (exhaust and non-exhaust) are the top two contributors to pseudo-ultrafine (<0.43 μm), fine (0.43–2.1 μm) and coarse mode (>2.1 μm) PM, respectively. Mass concentration of PM from coal and biomass combustion, industrial emissions, and diesel vehicle sources showed a bimodal size distribution, but gasoline vehicles and resuspended dust exhibited a peak in the fine and coarse mode, separately. Mass concentration of sulphate, nitrate and secondary organic aerosol exhibited a bimodal distribution and were correlated with temperature, indicating strong photochemical processing and repartitioning. High relative humidity related secondary aerosol was strongly associated with size shifts of PM, NO₃⁻ and SO₄²⁻ from the usual 0.43–0.65 μm to 1.1–2.1 μm. Our results demonstrated the dominance of primary combustion sources in the <0.43 μm particle mass, in contrast to that of secondary aerosol in fine particle mass, and dust in coarse particle mass in the Northern China megacity.

The rural domestic waste (RDW) compost has been widely used in agriculture and horticulture, but little is known about microplastics (MPs) in RDW composting. The current work deals with the abundance and characteristics of MPs in RDW composting, and the effects of composting processes on the composition of MPs. Compost samples from two RDW treatment stations were investigated, and a lab-scale experiment was carried out to verify the possible release of MPs from macroplastics (>25 mm) contained in the RDW during composting. MPs were identified using stereo-microscope and μ-FTIR. The average abundance of MPs (0.05–5 mm) in the RDW compost products was 2400 ± 358 items/kg (dry weight), and the main MPs shapes were fibers and films. Polyester, polypropylene (PP) and polyethylene (PE) were the most common polymer types. MPs having a size <1 mm accounted for more than 50% of the total quantity. With the progress of composting, the proportion of MPs having size <1 mm increased, and more foam MPs were observed in the late stage of composting. Under the influence of mechanical force, oxidation and biodegradation, a piece of expanded polystyrene (EPS), PP and PE macroplastic could release 4–63 MPs particles during the composting. Thus, the RDW compost was a significant source of MPs in soils, and the MPs in compost products were closely related to the quantity and type of plastic waste present in RDW, which helped to suggest better MPs control strategies.

The gut microbiota has been increasingly recognized to regulate host fitness, which in turn is dependent on stability of community structure and composition. Many biotic and abiotic factors have been demonstrated to shape gut microbiota of cladocerans. However, the interactive effects of these variables on cladocerans fitness due to alteration of gut microbiota and their linkage with life history parameters are poorly understood. Here, we investigated the responses of Daphnia magna gut microbiota to the combined effects of toxic Microcystis aeruginosa and high temperature and its associations with fitness. We found that under good food regime, the temperature has no effect on the composition of the gut microbiota, whereas under high proportion of toxic M. aeruginosa and high temperature conditions, D. magna lost their symbionts. High proportion of toxic M. aeruginosa and high temperature had synergistically negative effects on D. magna performance due to altered gut microbiota. The high abundance of symbiotic Comamonadaceae and good food increased D. magna fitness. The present study illustrates that understanding life history strategies in response to multiple stressors related to changes in the gut microbiota diversity and composition requires integrated approaches that incorporate multiple linked traits and tether them to one another.

Non-optimum ambient temperature has been associated with a variety of health outcomes in the elderly population. However, few studies have examined its adverse effects on neurocognitive function. In this study, we explored the temperature-cognition association in elderly women. We investigated 777 elderly women from the German SALIA cohort during the 2007–2010 follow-up. Cognitive function was evaluated using the CERAD-Plus test battery. Modelled data on daily weather conditions were assigned to the residential addresses. The temperature-cognition association over lag 0–10 days was estimated using multivariable regression with distributed lag non-linear model. The daily mean temperature ranged between −6.7 and 26.0 °C during the study period for the 777 participants. We observed an inverse U-shaped association in elderly women, with the optimum temperature (15.3 °C) located at the 68th percentile of the temperature range. The average z-score of global cognitive function declined by −0.31 (95%CI: 0.73, 0.11) for extreme cold (the 2.5th percentile of temperature range) and −0.92 (95%CI: 1.50, −0.33) for extreme heat (the 97.5th percentile of temperature range), in comparison to the optimum temperature. Episodic memory was more sensitive to heat exposure, while semantic memory and executive function were the two cognitive domains sensitive to cold exposure. Individuals living in an urban area and those with a low educational level were particularly sensitive to extreme heat. In summary, non-optimum temperature was inversely associated with cognitive function in elderly women, with the effect size for heat exposure particularly substantial. The strength of association varied by cognitive domains and individual characteristics.

Copper-containing antifouling paints (AFP) are widely used for leisure boat maintenance. Cu emitted from AFP into German surface water bodies has been suggested to be a significant source of heavy metal pollution, threatening water quality. We developed two scenarios to model Cu emissions from AFP applied on leisure boats on national scale, which allow identifying regional hotspots. The top-down approach (scenario A) was based on a previous study on national AFP consumption, while in the bottom-up approach (scenario B), median and interquartile range of Cu release rates depending on salinity conditions were considered for emission estimation. Both scenarios clearly highlighted the locally high emission pressure on inland waters in popular watersport regions, identifying these as requiring intense protection. Scenario B generally predicted lower Cu emissions (sea: 11.05–25.53 t a⁻¹, inland: 14.15–34.59 t a⁻¹) than scenario A (sea: 22.53 t a⁻¹, inland: 47.97 t a⁻¹). To evaluate their relevance, scenario results were compared to emissions modelled with MoRE (Modelling of Regionalized Emissions), which is used as reporting tool on substance emissions by Germany. According to scenarios A and B, the emission from AFP accounted for 13 % and 4–9 % of the total Cu emissions into inland waters in 2016, respectively. Scenario results were similar or higher than other emission pathways such as industrial direct dischargers. Thus, we consider Cu emissions from AFP as a significant pathway to be included in the MoRE emission inventory. We recommend scenario B for implementation as it allows a more flexible adaptation for future modelling.

Water quality monitoring programs often collect large amounts of data with limited attention given to the assessment of the dominant drivers of spatial and temporal water quality variations at the catchment scale. This study uses a multi-model approach: a) to identify the influential catchment characteristics affecting spatial variability in water quality; and b) to predict spatial variability in water quality more reliably and robustly. Tropical catchments in the Great Barrier Reef (GBR) area, Australia, were used as a case study. We developed statistical models using 58 catchment characteristics to predict the spatial variability in water quality in 32 GBR catchments. An exhaustive search method coupled with multi-model inference approaches were used to identify important catchment characteristics and predict the spatial variation in water quality across catchments. Bootstrapping and cross-validation approaches were used to assess the uncertainty in identified important factors and robustness of multi-model structure, respectively. The results indicate that water quality variables were generally most influenced by the natural characteristics of catchments (e.g., soil type and annual rainfall), while anthropogenic characteristics (i.e., land use) also showed significant influence on dissolved nutrient species (e.g., NOX, NH₄ and FRP). The multi-model structures developed in this work were able to predict average event-mean concentration well, with Nash-Sutcliffe coefficient ranging from 0.68 to 0.96. This work provides data-driven evidence for catchment managers, which can help them develop effective water quality management strategies.

Daunting amounts of microplastics are present in surface waters worldwide. A main category of microplastics is synthetic microfibers, which originate from textiles. These microplastics are generated and released in laundering and are discharged by wastewater treatment plants or enter surface waters from other sources. The polymers that constitute many common synthetic microfibers are mostly denser than water, and eventually settle out in aquatic environments. The interaction of these microfibers with submerged aquatic vegetation has not been thoroughly investigated but is potentially an important aquatic sink in surface waters. In the Laurentian Great Lakes, prolific growth of macrophytic Cladophora creates submerged biomass with a large amount of surface area and the potential to collect and concentrate microplastics. To determine the number of synthetic microfibers in Great Lakes Cladophora, samples were collected from Lakes Erie and Michigan at multiple depths in the spring and summer of 2018. After rinsing and processing the algae, associated synthetic microfibers were quantified. The average loads of synthetic microfibers determined from the Lake Erie and Lake Michigan samples were 32,000 per kg (dry weight (dw)) and 34,000 per kg (dw), respectively, 2–4 orders of magnitude greater than loads previously reported in water and sediment. To further explore this sequestration of microplastics, fresh and aged Cladophora were mixed with aqueous mixtures of microfibers or microplastic in the laboratory to simulate pollution events. Microscopic analyses indicated that fresh Cladophora algae readily interacted with microplastics via adsorptive forces and physical entanglement. These interactions mostly cease upon algal senescence, with an expected release of microplastics in benthic sediments. Collectively, these findings suggest that synthetic microfibers are widespread in Cladophora algae and the affinity between microplastics and Cladophora may offer insights for removing microplastic pollution.Macroalgae in the Laurentian Great Lakes contain high loads of synthetic microfibers, both entangled and adsorbed, which likely account for an important fraction of microplastics in these surface waters.

Since humans spend more than 90% of their time in indoor environments, indoor exposure can be an important non-dietary pathway to hazardous organic contaminants. It is thus important to characterize the chemical composition of indoor dust to assess the total contaminant exposure and estimate human health risks. The aim of this investigation was to perform a comprehensive chemical characterization of indoor dust. First, the robustness of an adopted extraction method using ultrasonication was evaluated for 85 target compounds. Thereafter, a workflow combining target analysis, suspect screening analysis (SSA) and nontarget analysis (NTA) was applied to dust samples from different indoor environments. Chemical analysis was performed using both gas chromatography and liquid chromatography coupled with high resolution mass spectrometry. Although suppressing matrix effects were prominent, target analysis enabled the quantification of organophosphate/brominated flame retardants (OPFRs/BFRs), liquid crystal monomers (LCMs), toluene diisocyanate, bisphenols, pesticides and tributyl citrate. The SSA confirmed the presence of OPFRs but also enabled the detection of polyethylene glycols (PEGs) and phthalates/parabens. The combination of hierarchical cluster analysis and scaled mass defect plots in the NTA workflow confirmed the presence of the above mentioned compounds, as well as detect other contaminants such as tetrabromobisphenol A, triclocarban, diclofenac and 3,5,6-trichloro-2-pyridinol, which were further confirmed using pure standards.

Severe fine particulate matter (PM₂.₅) pollution and the associated health risks remain pressing issues in the Yangtze River Delta (YRD), although significant efforts have been made locally, such as the Clean Air Action since 2013. Regional transport is an important contributor to high PM₂.₅ levels during haze episodes in the YRD, but its impact on human health is rarely analyzed. In this study, we evaluate the short-term PM₂.₅-related health risks and associated economic losses due to different source regions by estimating daily mortality based on model results in the YRD. The results show that regional transport induces significant health risks in the YRD during haze days, contributing over 60% of daily premature mortality in Shanghai and Nanjing (major cities in the YRD). Moreover, in Hangzhou and Jiaxing, regional transport’s contribution can be as high as 70%. The total daily mean economic loss in the YRD is estimated as 526.8 million Chinese Yuan (approximately 81.4 million U.S. dollar) in winter of 2015 and 2016, accounting for 1.4% of the daily averaged gross domestic product (GDP) of the YRD. Emission control (in accordance with the 13th Five-year Energy Conservation and Emission Reduction Plan) is an effective way to reduce health risks in the YRD, reducing premature deaths during haze days by 12–33%. More stringent emission control measures are suggested for further reduce PM₂.₅-related health risks.